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Qlik launched their new product Qlik Sense Desktop that officially marks the launch of their next generation platform. The Qlik community and practitioners had been waiting for Qlik.Next for a while and the launch of Qlik Sense Desktop marks the beginning of a new era for Qlik embracers.

The following steps describe the process of loading data from SSAS Tabular Model using Qlik Sense Desktop. As a pre-requisite, please ensure you have the necessary OLEDB drivers for SSAS (MSOLAP) installed on your desktop.

Step 1: In the ‘Data Load Editor’, click on ‘Create New Connection‘ and select OLEDB from the list of connections.

Step 2: Select the provider for Analysis Services and enter the connection details to connect to the tabular model. Click Save once done.

Step 3: Once the connection is successfully saved, it appears in the Data Connections pane on the right.

Step 4: Though the metadata can be viewed using the select data option, the OLEDB provider for SSAS cannot programmatically generate DAX queries. To extract data from the Tabular Model connection created in the previous step, DAX queries should be written in the data load editor as below.

The verdict is that there are subtle differences in the interface but there is no native SSAS connector in Qlik Sense desktop yet. There are major enhancements in the visualisation side of things and I’m sure a lot of us will be talking about them in the coming days.

QlikView does not have the ability to natively query SSAS cubes (both Multidimensional and Tabular). But it allows you to query SSAS using the Microsoft MSOLAP driver. The primary motive behind this post is the lack of material or content online about sourcing data from SSAS Tabular using DAX (SQL Server 2012). One could write MDX queries and extract data from SSAS Tabular, but that results in hours if not days for the query to execute and load a large dataset into a QlikView Data file (or QlikView Workbook).

Like this:

Most often we think that the cubes we design and implement will process without any issues when the corresponding dimensions and facts have sensible data. This, however, is only a myth. I learnt this the hard way when I modified an existing SSAS cube which had some changes to the dimension attributes. The processing of the cube failed due to a mismatch of an attribute’s data type between a dimension in the data source view (DSV) and the dimension in the cube. That’s when BIDS Helper came to my rescue. I quickly installed BIDS Helper from here and ran its inbuilt Dimension Health Check feature to discover the hidden truth. I found BIDS Helper to be extremely useful to perform health checks on measures as well.

As soon as I run this feature on my measure group, it points out that the data type of measures contained within the group can be changed for optimised results.

To keep this post short and quick, I would recommend BIDS Helper if you run into data-type problems when processing SSAS cubes.

You can download BIDS Helper and access the product’s documentation from the following Codeplex site: BIDS Helper